Agile governance, essential for managing rapid technological change and global scale of new technologies, involves systems thinking and design thinking for policy-making. It emphasizes multi-stakeholder participation, regulatory sandboxes for controlled experimentation, and data sharing for efficient regulation. India, with its digital public infrastructure, is well-positioned to lead in this agile governance approach.
India’s draft Personal Data Protection Bill has sparked debate over data localization, with the government insisting on processing personal data within the country. Unlike other nations that restrict data transfers, India has made localization the default, an approach seen as out of character with its global trade stance.
The McKinsey Digital India Report highlights India’s rapid digitization. With 560 million internet subscribers, it is second only to China. Despite a low Country Digital Adoption Index score of 32, India is digitizing faster than most countries - all the more reason for there to be fewer internet shutdowns.
There is value in large datasets that reveal statistically relevant insights - such as trends in fast food visits or sleep patterns. This is relevant to India’s growing data economy given the potential to use aggregated anonymous data to make informed decisions. We need to implement privacy by design, and for that organizations need to de-identify personal information to prevent potential harm if the data is lost or stolen.
Algorithms in streaming services and e-book libraries curate content based on individual preferences, often with impressive accuracy. However, the downside to this is the eventual homogenization of content. By continually reinforcing original preferences, the algorithms can lead to a lack of diversity in the content presented. We need to seek out new and different content, recognizing that while algorithms are powerful tools, they have limitations. They are only as good as the data they’ve been trained on, and without regular updates to keep them fresh and relevant, they can become restrictive rather than expansive in their recommendations.
Statistician Fredrick Hoffman, known for identifying health risks like asbestos and tobacco, is also remembered for his flawed 1896 study claiming African Americans were inherently sicker than whites. This study, influenced by prejudice, had lasting negative impacts. As we increasingly rely on data and predictive algorithms, it’s crucial to avoid such biases and ensure fair, accurate interpretations to prevent perpetuating discrimination and injustice.
Europe supplanted Asian dominance in the 1700s, thanks to the European discovery of ignorance and its subsequent pursuit of knowledge. There are parallels between this and today’s technological revolution, where virtual networks and global corporations have created a new form of influence, that are a modern form of colonization.
Data is a critical capital asset, driving major business transformations. Industries from retail to transportation are adopting data-driven strategies, with sensor technology and analytics optimizing performance and service. Governments are recognizing data’s value in smart city development and predictive policing, suggesting a future where data not only informs decisions but also automates regulatory compliance, potentially revolutionizing governance and business operations.
